How to integrate Bitbucket MCP with OpenAI Agents SDK

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Introduction

This guide walks you through connecting Bitbucket to the OpenAI Agents SDK using the Composio tool router. By the end, you'll have a working Bitbucket agent that can create a new branch off main, open a pull request for my feature, comment on the latest open issue, fetch readme file from repository through natural language commands.

This guide will help you understand how to give your OpenAI Agents SDK agent real control over a Bitbucket account through Composio's Bitbucket MCP server.

Before we dive in, let's take a quick look at the key ideas and tools involved.

TL;DR

Here's what you'll learn:
  • Get and set up your OpenAI and Composio API keys
  • Install the necessary dependencies
  • Initialize Composio and create a Tool Router session for Bitbucket
  • Configure an AI agent that can use Bitbucket as a tool
  • Run a live chat session where you can ask the agent to perform Bitbucket operations

What is open-ai-agents-sdk?

The OpenAI Agents SDK is a lightweight framework for building AI agents that can use tools and maintain conversation state. It provides a simple interface for creating agents with hosted MCP tool support.

Key features include:

  • Hosted MCP Tools: Connect to external services through hosted MCP endpoints
  • SQLite Sessions: Persist conversation history across interactions
  • Simple API: Clean interface with Agent, Runner, and tool configuration
  • Streaming Support: Real-time response streaming for interactive applications

What is the Bitbucket MCP server, and what's possible with it?

The Bitbucket MCP server is an implementation of the Model Context Protocol that connects your AI agent and assistants like Claude, Cursor, etc directly to your Bitbucket account. It provides structured and secure access to your repositories, issues, and pull requests, so your agent can create branches, manage issues, review code, and handle repository operations for you.

  • Branch and repository management: Let your agent create new branches for feature work or initialize fresh repositories within your Bitbucket workspace—no manual setup required.
  • Automated issue tracking: Have your agent create, comment on, or delete issues to streamline team collaboration and bug tracking directly from your workflows.
  • Pull request automation: Empower your agent to open new pull requests for code review, ensuring changes are properly tracked and integrated.
  • File and snippet operations: Ask your agent to fetch specific files from any branch or commit, or to post comments on code snippets for contextual discussions.
  • User profile and workspace insights: Retrieve your Bitbucket user profile details on demand, making it easy to personalize and audit agent-driven actions.

Supported Tools & Triggers

Tools
Create a branchCreates a new branch in a bitbucket repository from a target commit hash; the branch name must be unique, adhere to bitbucket's naming conventions, and not include the 'refs/heads/' prefix.
Create an issueCreates a new issue in a bitbucket repository, setting the authenticated user as reporter; ensures assignee (if provided) has repository access, and that any specified milestone, version, or component ids exist.
Create an issue commentAdds a new comment with markdown support to an existing bitbucket issue.
Create a pull requestCreates a new pull request in a specified bitbucket repository, ensuring the source branch exists and is distinct from the (optional) destination branch.
Create repositoryCreates a new bitbucket 'git' repository in a specified workspace, defaulting to the workspace's oldest project if `project key` is not provided.
Create snippet commentPosts a new top-level comment or a threaded reply to an existing comment on a specified bitbucket snippet.
Delete issuePermanently deletes a specific issue, identified by its `issue id`, from the repository specified by `repo slug` within the given `workspace`.
Delete repositoryPermanently deletes a specified bitbucket repository; this action is irreversible and does not affect forks.
Get current userRetrieves the profile information (uuid, display name, links, creation date) for the currently authenticated bitbucket user.
Get file from repositoryRetrieves a specific file's content from a bitbucket repository at a given commit (hash, branch, or tag), failing if the file path is invalid for that commit.
Get Pull RequestGet a single pull request by id with complete details.
Get snippetRetrieves a specific bitbucket snippet by its encoded id from an existing workspace, returning its metadata and file structure.
List pull requestsLists pull requests in a specified, accessible bitbucket repository, optionally filtering by state (open, merged, declined).
List repositories in workspaceLists repositories in a specified bitbucket workspace, accessible to the authenticated user, with options to filter by role or query string, and sort results.
List workspace membersLists all members of a specified bitbucket workspace; the workspace must exist.
List workspacesLists bitbucket workspaces accessible to the authenticated user, optionally filtered and sorted.
Update an issueUpdates an existing issue in a bitbucket repository by modifying specified attributes; requires `workspace`, `repo slug`, `issue id`, and at least one attribute to update.

What is the Composio tool router, and how does it fit here?

What is Tool Router?

Composio's Tool Router helps agents find the right tools for a task at runtime. You can plug in multiple toolkits (like Gmail, HubSpot, and GitHub), and the agent will identify the relevant app and action to complete multi-step workflows. This can reduce token usage and improve the reliability of tool calls. Read more here: Getting started with Tool Router

The tool router generates a secure MCP URL that your agents can access to perform actions.

How the Tool Router works

The Tool Router follows a three-phase workflow:

  1. Discovery: Searches for tools matching your task and returns relevant toolkits with their details.
  2. Authentication: Checks for active connections. If missing, creates an auth config and returns a connection URL via Auth Link.
  3. Execution: Executes the action using the authenticated connection.

Step-by-step Guide

Prerequisites

Before starting, make sure you have:
  • Composio API Key and OpenAI API Key
  • Primary know-how of OpenAI Agents SDK
  • A live Bitbucket project
  • Some knowledge of Python or Typescript

Getting API Keys for OpenAI and Composio

OpenAI API Key
  • Go to the OpenAI dashboard and create an API key. You'll need credits to use the models, or you can connect to another model provider.
  • Keep the API key safe.
Composio API Key

Install dependencies

pip install composio_openai_agents openai-agents python-dotenv

Install the Composio SDK and the OpenAI Agents SDK.

Set up environment variables

bash
OPENAI_API_KEY=sk-...your-api-key
COMPOSIO_API_KEY=your-api-key
USER_ID=composio_user@gmail.com

Create a .env file and add your OpenAI and Composio API keys.

Import dependencies

import asyncio
import os
from dotenv import load_dotenv

from composio import Composio
from composio_openai_agents import OpenAIAgentsProvider
from agents import Agent, Runner, HostedMCPTool, SQLiteSession
What's happening:
  • You're importing all necessary libraries.
  • The Composio and OpenAIAgentsProvider classes are imported to connect your OpenAI agent to Composio tools like Bitbucket.

Set up the Composio instance

load_dotenv()

api_key = os.getenv("COMPOSIO_API_KEY")
user_id = os.getenv("USER_ID")

if not api_key:
    raise RuntimeError("COMPOSIO_API_KEY is not set. Create a .env file with COMPOSIO_API_KEY=your_key")

# Initialize Composio
composio = Composio(api_key=api_key, provider=OpenAIAgentsProvider())
What's happening:
  • load_dotenv() loads your .env file so OPENAI_API_KEY and COMPOSIO_API_KEY are available as environment variables.
  • Creating a Composio instance using the API Key and OpenAIAgentsProvider class.

Create a Tool Router session

# Create a Bitbucket Tool Router session
session = composio.create(
    user_id=user_id,
    toolkits=["bitbucket"]
)

mcp_url = session.mcp.url

What is happening:

  • You give the Tool Router the user id and the toolkits you want available. Here, it is only bitbucket.
  • The router checks the user's Bitbucket connection and prepares the MCP endpoint.
  • The returned session.mcp.url is the MCP URL that your agent will use to access Bitbucket.
  • This approach keeps things lightweight and lets the agent request Bitbucket tools only when needed during the conversation.

Configure the agent

# Configure agent with MCP tool
agent = Agent(
    name="Assistant",
    model="gpt-5",
    instructions=(
        "You are a helpful assistant that can access Bitbucket. "
        "Help users perform Bitbucket operations through natural language."
    ),
    tools=[
        HostedMCPTool(
            tool_config={
                "type": "mcp",
                "server_label": "tool_router",
                "server_url": mcp_url,
                "headers": {"x-api-key": api_key},
                "require_approval": "never",
            }
        )
    ],
)
What's happening:
  • We're creating an Agent instance with a name, model (gpt-5), and clear instructions about its purpose.
  • The agent's instructions tell it that it can access Bitbucket and help with queries, inserts, updates, authentication, and fetching database information.
  • The tools array includes a HostedMCPTool that connects to the MCP server URL we created earlier.
  • The headers dict includes the Composio API key for secure authentication with the MCP server.
  • require_approval: 'never' means the agent can execute Bitbucket operations without asking for permission each time, making interactions smoother.

Start chat loop and handle conversation

print("\nComposio Tool Router session created.")

chat_session = SQLiteSession("conversation_openai_toolrouter")

print("\nChat started. Type your requests below.")
print("Commands: 'exit', 'quit', or 'q' to end\n")

async def main():
    try:
        result = await Runner.run(
            agent,
            "What can you help me with?",
            session=chat_session
        )
        print(f"Assistant: {result.final_output}\n")
    except Exception as e:
        print(f"Error: {e}\n")

    while True:
        user_input = input("You: ").strip()
        if user_input.lower() in {"exit", "quit", "q"}:
            print("Goodbye!")
            break

        result = await Runner.run(
            agent,
            user_input,
            session=chat_session
        )
        print(f"Assistant: {result.final_output}\n")

asyncio.run(main())
What's happening:
  • The program prints a session URL that you visit to authorize Bitbucket.
  • After authorization, the chat begins.
  • Each message you type is processed by the agent using Runner.run().
  • The responses are printed to the console, and conversations are saved locally using SQLite.
  • Typing exit, quit, or q cleanly ends the chat.

Complete Code

Here's the complete code to get you started with Bitbucket and open-ai-agents-sdk:

import asyncio
import os
from dotenv import load_dotenv

from composio import Composio
from composio_openai_agents import OpenAIAgentsProvider
from agents import Agent, Runner, HostedMCPTool, SQLiteSession

load_dotenv()

api_key = os.getenv("COMPOSIO_API_KEY")
user_id = os.getenv("USER_ID")

if not api_key:
    raise RuntimeError("COMPOSIO_API_KEY is not set. Create a .env file with COMPOSIO_API_KEY=your_key")

# Initialize Composio
composio = Composio(api_key=api_key, provider=OpenAIAgentsProvider())

# Create Tool Router session
session = composio.create(
    user_id=user_id,
    toolkits=["bitbucket"]
)
mcp_url = session.mcp.url

# Configure agent with MCP tool
agent = Agent(
    name="Assistant",
    model="gpt-5",
    instructions=(
        "You are a helpful assistant that can access Bitbucket. "
        "Help users perform Bitbucket operations through natural language."
    ),
    tools=[
        HostedMCPTool(
            tool_config={
                "type": "mcp",
                "server_label": "tool_router",
                "server_url": mcp_url,
                "headers": {"x-api-key": api_key},
                "require_approval": "never",
            }
        )
    ],
)

print("\nComposio Tool Router session created.")

chat_session = SQLiteSession("conversation_openai_toolrouter")

print("\nChat started. Type your requests below.")
print("Commands: 'exit', 'quit', or 'q' to end\n")

async def main():
    try:
        result = await Runner.run(
            agent,
            "What can you help me with?",
            session=chat_session
        )
        print(f"Assistant: {result.final_output}\n")
    except Exception as e:
        print(f"Error: {e}\n")

    while True:
        user_input = input("You: ").strip()
        if user_input.lower() in {"exit", "quit", "q"}:
            print("Goodbye!")
            break

        result = await Runner.run(
            agent,
            user_input,
            session=chat_session
        )
        print(f"Assistant: {result.final_output}\n")

asyncio.run(main())

Conclusion

This was a starter code for integrating Bitbucket MCP with OpenAI Agents SDK to build a functional AI agent that can interact with Bitbucket.

Key features:

  • Hosted MCP tool integration through Composio's Tool Router
  • SQLite session persistence for conversation history
  • Simple async chat loop for interactive testing
You can extend this by adding more toolkits, implementing custom business logic, or building a web interface around the agent.

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CrewAI

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Use Bitbucket MCP with CrewAI

FAQ

What are the differences in Tool Router MCP and Bitbucket MCP?

With a standalone Bitbucket MCP server, the agents and LLMs can only access a fixed set of Bitbucket tools tied to that server. However, with the Composio Tool Router, agents can dynamically load tools from Bitbucket and many other apps based on the task at hand, all through a single MCP endpoint.

Can I use Tool Router MCP with OpenAI Agents SDK?

Yes, you can. OpenAI Agents SDK fully supports MCP integration. You get structured tool calling, message history handling, and model orchestration while Tool Router takes care of discovering and serving the right Bitbucket tools.

Can I manage the permissions and scopes for Bitbucket while using Tool Router?

Yes, absolutely. You can configure which Bitbucket scopes and actions are allowed when connecting your account to Composio. You can also bring your own OAuth credentials or API configuration so you keep full control over what the agent can do.

How safe is my data with Composio Tool Router?

All sensitive data such as tokens, keys, and configuration is fully encrypted at rest and in transit. Composio is SOC 2 Type 2 compliant and follows strict security practices so your Bitbucket data and credentials are handled as safely as possible.

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